Curriculum
10 Sections
40 Lessons
10 Weeks
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Introduction to Prompt Engineering
4
1.1
What is prompt engineering
1.2
Importance in AI workflows
1.3
Business use cases
1.4
Prompt vs traditional automation
Understanding AI Models & Prompts
4
2.1
How language models work
2.2
Input-output behavior
2.3
Prompt structure basics
2.4
Temperature and token settings
Writing Effective Prompts
4
3.1
Clarity and context
3.2
Role-based prompting
3.3
Step-by-step prompts
3.4
Refining through iteration
Prompting for Business Tasks
4
4.1
Email & report drafting
4.2
Meeting summaries
4.3
Market research & analysis
4.4
Product descriptions
Prompting for Productivity
4
5.1
Task automation
5.2
Data cleaning & sorting
5.3
Brainstorming ideas
5.4
Document formatting
Prompting for Customer Service
4
6.1
Auto-reply generation
6.2
FAQ building
6.3
Tone control prompts
6.4
Escalation and intent detection
Prompting for Marketing & Sales
4
7.1
Ad copy generation
7.2
Social media content
7.3
Landing page drafts
7.4
Lead follow-up messages
Prompt Engineering Best Practices
4
8.1
Few-shot vs zero-shot prompting
8.2
Reusability of prompts
8.3
Testing and evaluation
8.4
Common mistakes to avoid
Hands-on Prompting Exercises
4
9.1
Real-world business scenarios
9.2
Improving existing prompts
9.3
Comparing outputs
9.4
Mini case studies
Tools & Platforms for Prompting
4
10.1
ChatGPT & alternatives
10.2
Prompt libraries and templates
10.3
Business integrations (Zapier, Notion, etc.)
10.4
AI APIs and custom apps
Prompt Engineering for Business
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